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Model Independent Approach of the JUNO 8B Solar Neutrino Program

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arXiv 2022年

作者： Zhao, Jie Yue, Baobiao Lu, Haoqi Li, Yufeng Ling, Jiajie Yu, Zeyuan Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad Aleem, Abid Alexandros, Tsagkarakis An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Bai, Weidong Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Bergnoli, Antonio Birkenfeld, Thilo Blin, Sylvie Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Busto, Jose Butorov, Ilya Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callegari, Riccardo Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chan, Chi Chang, Jinfan Chang, Yun Chen, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Cheng, Jie Cheng, Yaping Chepurnov, Alexander Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Molla, Marta Colomer Di Lorenzo, Selma Conforti Corti, Daniele Dal Corso, Flavio Dalager, Olivia De La Taille, Christophe Deng, Zhi Deng, Ziyan Depnering, Wilfried Diaz, Marco Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dusini, Stefano Dvorak, Martin Enqvist, Timo Enzmann, Heike Fabbri, Andrea Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Fei, Zhengyong Feng, Li-Cheng Feng, Qichun Ford, Richard Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Gromov, Maxim Gromov, Vasi Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil ANID Chile Pontificia Universidad Católica de Chile Santiago Chile Universidad Tecnica Federico Santa Maria Valparaiso Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China Harbin Institute of Technology Harbin China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao China Institute of Modern Physics Chinese Academy of Sciences Lanzhou China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological Sciences Shijiazhuang China Nankai University Tianjin China Wuhan University Wuhan China Xi'an Jiaotong University Xi'An China Xiamen Unive

The physics potential of detecting 8B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model independent manner by using three distinct channels of the charged-current (CC), neutral-current (NC) and elastic scattering (ES) interactions. Due to the largest-ever mass of 13C nuclei in the liquid-scintillator detectors and the expected low background level, 8B solar neutrinos would be observable in the CC and NC interactions on 13C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC and ES channels to guarantee the 8B solar neutrino observation. From the sensitivity studies performed in this work, we show that JUNO, with ten years of data, can reach the 1σ precision levels of 5%, 8% and 20% for the 8B neutrino flux, sin2 θ12, and ∆m221, respectively. It would be unique and helpful to probe the details of both solar physics and neutrino physics. In addition, when combined with SNO, the world-best precision of 3% is expected for the 8B neutrino flux measurement. © 2022, CC BY.

关键词： Neutrons

JUNO Sensitivity on Proton Decay p → ν¯K+ Searches

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arXiv 2022年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Bergnoli, Antonio Birkenfeld, Thilo Blin, Sylvie Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Buscemi, Mario Busto, Jose Butorov, Ilya Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callegari, Riccardo Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chang, Jinfan Chang, Yun Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Cheng, Jie Cheng, Yaping Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Di Lorenzo, Selma Conforti Corti, Daniele Corso, Flavio Dal Dalager, Olivia De La Taille, Christophe Deng, Zhi Deng, Ziyan Depnering, Wilfried Diaz, Marco Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dusini, Stefano Dvorak, Martin Enqvist, Timo Enzmann, Heike Fabbri, Andrea Fahrendholz, Ulrike Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Feng, Li-Cheng Feng, Qichun Ford, Richard Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giaz, Agnese Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Grewing, Christian Gromov, Vasily Gu, Minghao Gu, Xiaofei Gu, Yu Guan, Mengyun Guardone, Nunzio Gul, Maria Guo, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Hackspache Pontificia Universidad Católica de Chile Santiago Chile IPHC Université de Strasbourg CNRS IN2P3 StrasbourgF-67037 France Pakistan Institute of Nuclear Science and Technology Islamabad Pakistan INFN Catania and Dipartimento di Fisica e Astronomia Università di Catania Catania Italy East China University of Science and Technology Shanghai China University of Science and Technology of China Hefei China Joint Institute for Nuclear Research Dubna Russia INFN Sezione di Milano Dipartimento di Fisica Università di Milano Milano Italy Department of Physics Faculty of Science Chulalongkorn University Bangkok Thailand IJCLab Université Paris-Saclay CNRS IN2P3 Orsay91405 France Department of Physics and Earth Science University of Ferrara INFN Sezione di Ferrara Ferrara Italy INFN Milano Bicocca University of Milano Bicocca Milano Italy INFN Sezione di Padova Padova Italy III. Physikalisches Institut B RWTH Aachen University Aachen Germany Eberhard Karls Universität Tübingen Physikalisches Institut Tübingen Germany Institute of High Energy Physics Beijing China SUBATECH Université de Nantes IMT Atlantique CNRS-IN2P3 Nantes France Univ. Bordeaux CNRS LP2I UMR 5797 GradignanF-33170 France Department of Physics National Taiwan University Taipei Taiwan Dipartimento di Fisica e Astronomia Università di Padova INFN Sezione di Padova Padova Italy University of Roma Tre INFN Sezione Roma Tre Roma Italy Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Wuhan University Wuhan China INFN Milano Bicocca Politecnico of Milano Milano Italy National United University Miao-Li Taiwan Dongguan University of Technology Dongguan China Tsinghua University Beijing China Institute of Modern Physics Chinese Academy of Sciences Lanzhou China Institute of Physics National Yang Ming Chiao Tung University Hsinchu Taiwan North China Electric Power University Beijing China Sun Yat-Sen University Guangzhou China Beijing Institute of Spacecraft Environment

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in p → ν¯K+ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via p → ν¯K+ is 36.9% ± 4.9% with a background level of 0.2 ± 0.05(syst) ± 0.2(stat) events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is 9.6 × 1033 years, which is competitive with the current best limits on the proton lifetime in this channel and complementary using different detection technologies. © 2022, CC BY-NC-SA.

关键词：

Sub-percent Precision Measurement of Neutrino Oscillation Parameters with JUNO

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arXiv 2022年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad Aleem, Abid Alexandros, Tsagkarakis An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Bai, Weidong Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Bergnoli, Antonio Birkenfeld, Thilo Blin, Sylvie Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Busto, Jose Butorov, Ilya Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callegari, Riccardo Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chan, Chi Chang, Jinfan Chang, Yun Chen, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Cheng, Jie Cheng, Yaping Cheng, Yu Chin Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Di Lorenzo, Selma Conforti Corti, Daniele Dal Corso, Flavio Dalager, Olivia De La Taille, Christophe Deng, Zhi Deng, Ziyan Depnering, Wilfried Diaz, Marco Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dusini, Stefano Dvorak, Martin Enqvist, Timo Enzmann, Heike Fabbri, Andrea Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Fei, Zhengyong Feng, Li-Cheng Feng, Qichun Ford, Richard Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Gromov, Vasily Gu, Minghao Gu, Xiaofei Gu, Yu Guan, Mengyun Guan, Yuduo Guardone, Nunzio Guo, Cong Guo, Jingyuan Guo, Wan Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil Pontificia Universidad Católica de Chile Santiago Chile Universidad Tecnica Federico Santa Maria Valparaiso Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China Harbin Institute of Technology Harbin China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao China Institute of Modern Physics Chinese Academy of Sciences Lanzhou China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological Sciences Shijiazhuang China Nankai University Tianjin China Wuhan University Wuhan China Xi’an Jiaotong University Xi’an China Xiamen University Xiamen

JUNO is a multi-purpose neutrino observatory under construction in the south of China. This publication presents new sensitivity estimates for the measurement of the ∆m231, ∆m221, sin2 θ12, and sin2 θ13 oscillation parameters using reactor antineutrinos, which is one of the primary physics goals of the experiment. The sensitivities are obtained using the best knowledge available to date on the location and overburden of the experimental site, the nuclear reactors in the surrounding area and beyond, the detector response uncertainties, and the reactor antineutrino spectral shape constraints expected from the TAO satellite detector. It is found that the ∆m231, ∆m221, and sin2 θ12 oscillation parameters will be determined to better than 0.5% precision in six years of data collection, which represents approximately an order of magnitude improvement over existing constraints. © 2022, CC BY.

关键词： Nuclear reactors

Prospects for Detecting the Diffuse Supernova Neutrino Background with JUNO

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arXiv 2022年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Bergnoli, Antonio Birkenfeld, Thilo Blin, Sylvie Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Buscemi, Mario Busto, Jose Butorov, Ilya Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callegari, Riccardo Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chang, Jinfan Chang, Yun Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yi-Wen Chen, Yixue Chen, Yu Chen, Zhang Cheng, Jie Cheng, Yaping Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Di Lorenzo, Selma Conforti Corti, Daniele Dal Corso, Flavio Dalager, Olivia De La Taille, Christophe Deng, Zhi Deng, Ziyan Depnering, Wilfried Diaz, Marco Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dusini, Stefano Dvorak, Martin Enqvist, Timo Enzmann, Heike Fabbri, Andrea Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Feng, Li-Cheng Feng, Qichun Ford, Richard Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giaz, Agnese Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Gromov, Vasily Gu, Minghao Gu, Xiaofei Gu, Yu Guan, Mengyun Guardone, Nunzio Gul, Maria Guo, Cong Guo, Jingyuan Guo, Wanlei Guo, Xinheng Guo, Yuhang Hackspacher, Paul Hagner, Caren Han, Ran Han, Yan Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil ANID Chile Pontificia Universidad Católica de Chile Santiago Chile Universidad Tecnica Federico Santa Maria Valparaiso Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China Harbin Institute of Technology Harbin China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation Ministry of Education Shandong University Qingdao China Institute of Modern Physics Chinese Academy of Sciences Lanzhou China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Institute of Hydrogeology and Environmental Geology Chinese Academy of Geological Sciences Shijiazhuang China Nankai University Tianjin China Wuhan University Wuhan China Xi'an Jiaotong University Xi'An China Xiamen Univers

We present the detection potential for the diffuse supernova neutrino background (DSNB) at the Jiangmen Underground Neutrino Observatory (JUNO), using the inverse-beta-decay (IBD) detection channel on free protons. We employ the latest information on the DSNB flux predictions, and investigate in detail the background and its reduction for the DSNB search at JUNO. The atmospheric neutrino induced neutral current (NC) background turns out to be the most critical background, whose uncertainty is carefully evaluated from both the spread of model predictions and an envisaged in situ measurement. We also make a careful study on the background suppression with the pulse shape discrimination (PSD) and triple coincidence (TC) cuts. With latest DSNB signal predictions, more realistic background evaluation and PSD efficiency optimization, and additional TC cut, JUNO can reach the significance of 3σ for 3 years of data taking, and achieve better than 5σ after 10 years for a reference DSNB model. In the pessimistic scenario of non-observation, JUNO would strongly improve the limits and exclude a significant region of the model parameter space. © 2022, CC BY.

关键词： Forecasting

Research on the retinal vascular image segmentation algorithm 5

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Research on the retinal vascular image segmentation algorith...

5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017

作者： Zhang, Lijuan Yin, Tingting Li, Dongming Su, Zhengbo Su, Wei College of Computer Science and Engineering Changchun University of Technology Changchun130012 China School of Information Technology Jilin Agricultural University Changchun130118 China School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Informatization Center Changchun University of Science and Technology Changchun130022 China

In this paper, a multi-scale segmentation method for retinal vascular image which is based on statistical mixture model is proposed. Firstly, the image field of view is extracted by YIQ spatial brightness information. Then, we enhance the feature of blood vessel image by using Gaussian function and Hessian matrix to construct multi-scale enhancement filter. Finally, a fixed mixture model which consists of Gaussian and exponential model is used to fit the vessel image, and the blood vessel image is separated by a maximum posterior probability classification. To validate our proposed algorithm, the segmentation experiments are performed for the vessel image in the DRIVE database. The segmentation results are compared with other algorithms, and using accuracy, sensitivity, and specificity as the objective evaluation criteria. The experimental results show that our algorithm produces accurate retinal vascular image segmentation results.

关键词： Image segmentation

Wavelet-based curvelet transform for turbulence degraded image denoising 5

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Wavelet-based curvelet transform for turbulence degraded ima...

5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017

作者： Zhang, Lijuan Qiu, Huan Li, Dongming Su, Zhengbo Su, Wei College of Computer Science and Engineering Changchun University of Technology Changchun130012 China School of Information Technology Jilin Agricultural University Changchun130118 China School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China Informatization Center Changchun University of Science and Technology Changchun130022 China

In this paper, we present a wavelet-based Curvelet transform method for turbulence degraded image denoising. Wavelet transform is good for local analysis, and Curvelet transform based on a Wrapping method can be very good sparse representation for image edge details. First, we decompose the turbulent degraded image using the 2-D discrete wavelet transform, and extract the low and high frequency coefficients;Then on this basis, the high frequency coefficients will be used for the Curvelet transform based on a Wrapping method, and we improve the threshold selection method using a soft threshold method to trim the Curvelet coefficients;Finally, we provide the specific implementation steps of this algorithm. We evaluate our algorithm using the discrete cosine transform (DCT) algorithm and wavelet analysis algorithm as a benchmark. Using simulated turbulence degraded images, we show that our approach exhibits better performance in peak signal-to-noise ratio (PSNR), mean square error (MSE), and visual quality, which has a certain application value for turbulence degraded image denoising.

关键词： Image denoising

Mass Testing and Characterization of 20-inch PMTs for JUNO

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arXiv 2022年

作者： Abusleme, Angel Adam, Thomas Ahmad, Shakeel Ahmed, Rizwan Aiello, Sebastiano Akram, Muhammad Aleem, Abid Alexandros, Tsagkarakis An, Fengpeng An, Qi Andronico, Giuseppe Anfimov, Nikolay Antonelli, Vito Antoshkina, Tatiana Asavapibhop, Burin de André, João Pedro Athayde Marcondes Auguste, Didier Bai, Weidong Balashov, Nikita Baldini, Wander Barresi, Andrea Basilico, Davide Baussan, Eric Bellato, Marco Bergnoli, Antonio Birkenfeld, Thilo Blin, Sylvie Blum, David Blyth, Simon Bolshakova, Anastasia Bongrand, Mathieu Bordereau, Clément Breton, Dominique Brigatti, Augusto Brugnera, Riccardo Bruno, Riccardo Budano, Antonio Busto, Jose Butorov, Ilya Cabrera, Anatael Caccianiga, Barbara Cai, Hao Cai, Xiao Cai, Yanke Cai, Zhiyan Callegari, Riccardo Cammi, Antonio Campeny, Agustin Cao, Chuanya Cao, Guofu Cao, Jun Caruso, Rossella Cerna, Cédric Chan, Chi Chang, Jinfan Chang, Yun Chen, Guoming Chen, Pingping Chen, Po-An Chen, Shaomin Chen, Xurong Chen, Yixue Chen, Yu Chen, Zhiyuan Chen, Zikang Cheng, Jie Cheng, Yaping Cheng, Yu Chin Chetverikov, Alexey Chiesa, Davide Chimenti, Pietro Chukanov, Artem Claverie, Gérard Clementi, Catia Clerbaux, Barbara Molla, Marta Colomer Di Lorenzo, Selma Conforti Corti, Daniele Corso, Flavio Dal Dalager, Olivia De La Taille, Christophe Deng, Zhi Deng, Ziyan Depnering, Wilfried Diaz, Marco Ding, Xuefeng Ding, Yayun Dirgantara, Bayu Dmitrievsky, Sergey Dohnal, Tadeas Dolzhikov, Dmitry Donchenko, Georgy Dong, Jianmeng Doroshkevich, Evgeny Dracos, Marcos Druillole, Frédéric Du, Ran Du, Shuxian Dusini, Stefano Dvorak, Martin Enqvist, Timo Enzmann, Heike Fabbri, Andrea Fan, Donghua Fan, Lei Fang, Jian Fang, Wenxing Fargetta, Marco Fedoseev, Dmitry Fei, Zhengyong Feng, Li-Cheng Feng, Qichun Ford, Richard Fournier, Amélie Gan, Haonan Gao, Feng Garfagnini, Alberto Gavrikov, Arsenii Giammarchi, Marco Giudice, Nunzio Gonchar, Maxim Gong, Guanghua Gong, Hui Gornushkin, Yuri Göttel, Alexandre Grassi, Marco Gromov, Vasily Gu, Minghao Gu, Xiaofei Gu, Yu Guan, Mengyun Guan, Yuduo Guardone, Nunzio Guo, Cong G Yerevan Physics Institute Yerevan Armenia Université Libre de Bruxelles Brussels Belgium Universidade Estadual de Londrina Londrina Brazil Pontificia Universidade Catolica do Rio de Janeiro Rio de Janeiro Brazil ANID Chile Pontificia Universidad Católica de Chile Santiago Chile Universidad Tecnica Federico Santa Maria Valparaiso Chile Beijing Institute of Spacecraft Environment Engineering Beijing China Beijing Normal University Beijing China China Institute of Atomic Energy Beijing China Institute of High Energy Physics Beijing China North China Electric Power University Beijing China School of Physics Peking University Beijing China Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Jilin University Changchun China College of Electronic Science and Engineering National University of Defense Technology Changsha China Chongqing University Chongqing China Dongguan University of Technology Dongguan China Jinan University Guangzhou China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China The Radiochemistry and Nuclear Chemistry Group University of South China Hengyang China Wuyi University Jiangmen China Shandong University Jinan China Key Laboratory of Particle Physics and Particle Irradiation Ministry of Education Shandong University Qingdao China Institute of Modern Physics Chinese Academy of Sciences Lanzhou China Nanjing University Nanjing China Guangxi University Nanning China East China University of Science and Technology Shanghai China School of Physics and Astronomy Shanghai Jiao Tong University Shanghai China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai China Nankai University Tianjin China Wuhan University Wuhan China Xi’an Jiaotong University Xi'An China Xiamen University Xiamen China School of Physics and Microelectronics Zhengzhou University Zhengzhou China Institute of Physics National Yang Ming Chiao Tung Universit

Main goal of the JUNO experiment is to determine the neutrino mass ordering using a 20 kt liquid-scintillator detector. Its key feature is an excellent energy resolution of at least 3 % at 1 MeV, for which its instruments need to meet a certain quality and thus have to be fully characterized. More than 20,000 20-inch PMTs have been received and assessed by JUNO after a detailed testing program which began in 2017 and elapsed for about four years. Based on this mass characterization and a set of specific requirements, a good quality of all accepted PMTs could be ascertained. This paper presents the performed testing procedure with the designed testing systems as well as the statistical characteristics of all 20-inch PMTs intended to be used in the JUNO experiment, covering more than fifteen performance parameters including the photocathode uniformity. This constitutes the largest sample of 20-inch PMTs ever produced and studied in detail to date, i.e. 15,000 of the newly developed 20-inch MCP-PMTs from Northern Night Vision Technology Co. (NNVT) and 5,000 of dynode PMTs from Hamamatsu Photonics K. K.(HPK). © 2022, CC BY.

关键词： Photons

Focus Measure Based on the Image Moments

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Focus Measure Based on the Image Moments

IEEE International Conference on Mechatronics and Automation

作者： Liqiang Guo Lian Liu Haijiang Sun School of Computer Science and Technology Huaiyin Normal University Huai'an Jiangsu Province China School of Physics and Electronic Electrical Engineering Huaiyin Normal University Huai'an Jiangsu Province China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academic Sciences Changchun Jilin Province China

Focus measure plays an important role in the passive optical imaging systems. However, most of existing focus measure is prone to be affected under the noisy conditions. In this study, we proposed a novel focus measure by using the blocked image moment functions and variance statistics. We first divide the image into 8×8 non-overlapping blocks, and compute the Chebyshev moment T_(11) for each image blocks, then use the statistical method to construct the focus measure. The experimental results under different noisy conditions indicate the robustness of the proposed focus measure.

关键词： Focus measure Blocked image moments Noise insensitive

A model of counterplanning with variable object set

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A model of counterplanning with variable object set

2017 Asia-Pacific Computational Intelligence and Information Technology Conference

作者： Ying Liu Dantong Ouyang Wenxiang Gu Lei Wang College of Computer Science and Technology Jilin University College of Humanities & Science of Northeast Normal University Changchun Architecture & Civil Engineering College

In recent years,the research for the counterplanning and the planning with variable object set has been regarded as difficult *** this paper,we effectively combine them under the graphplan framework,and provide a model of counterplanning with variable object *** can create beneficial objects and delete useless objects,so as to achieve the goals of our agents and block or stop adversarial agents' *** model can be widely used in intrusion detection system,network security,military area,commercial battlefield,and other fields.

关键词： Active agent A model of counterplanning with variable object set